本文整理汇总了Python中numpy.random.negative_binomial方法的典型用法代码示例。如果您正苦于以下问题：Python random.negative_binomial方法的具体用法？Python random.negative_binomial怎么用？Python random.negative_binomial使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类numpy.random的用法示例。
在下文中一共展示了random.negative_binomial方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: get_example_data
# 需要导入模块: from numpy import random [as 别名]
# 或者: from numpy.random import negative_binomial [as 别名]
def get_example_data(*, sparse=False):
# create test object
adata = AnnData(np.multiply(binomial(1, 0.15, (100, 20)), negative_binomial(2, 0.25, (100, 20))))
# adapt marker_genes for cluster (so as to have some form of reasonable input
adata.X[0:10, 0:5] = np.multiply(binomial(1, 0.9, (10, 5)), negative_binomial(1, 0.5, (10, 5)))
# The following construction is inefficient, but makes sure that the same data is used in the sparse case
if sparse:
adata.X = sp.csr_matrix(adata.X)
# Create cluster according to groups
adata.obs['true_groups'] = pd.Categorical(np.concatenate((
np.zeros((10,), dtype=int),
np.ones((90,), dtype=int),
)))
return adata 示例2: sample_binomial_frag_len
# 需要导入模块: from numpy import random [as 别名]
# 或者: from numpy.random import negative_binomial [as 别名]
def sample_binomial_frag_len(frag_mean=200, frag_variance=100):
"""
Sample a fragment length from a binomial distribution parameterized with a
mean and variance.
If frag_variance > frag_mean, use a Negative-Binomial distribution.
"""
assert(abs(frag_mean - frag_variance) > 1)
if frag_variance < frag_mean:
p = 1 - (frag_variance/float(frag_mean))
# N = mu/(1-(sigma^2/mu))
n = float(frag_mean) / (1 - (float(frag_variance)/float(frag_mean)))
return binomial(n, p)
else:
r = -1 * (power(frag_mean, 2)/float(frag_mean - frag_variance))
p = frag_mean / float(frag_variance)
print "Sampling frag_mean=",frag_mean, " frag_variance=", frag_variance
print "r: ",r, " p: ", p
return negative_binomial(r, p) 示例3: rvs
# 需要导入模块: from numpy import random [as 别名]
# 或者: from numpy.random import negative_binomial [as 别名]
def rvs(self, size=None):
return random.negative_binomial(self.n, self.p, size=size) 示例4: simulate_BNB
# 需要导入模块: from numpy import random [as 别名]
# 或者: from numpy.random import negative_binomial [as 别名]
def simulate_BNB(mean, sigma, n):
# sys.stderr.write("%g %g %g\n" % (mean, sigma, n))
mean_p = np.float64(n) / (n+mean)
sigma = (1 / sigma)**2
a = mean_p * (sigma)+1
b = (1 - mean_p)*sigma
p = beta(a, b)
#sys.stderr.write("%f %f\n"%(n,p))
counts = negative_binomial(n, p)
return counts